The invention is applicable in systems wherein multiple users simultaneously make use of a common carrier or use distinct carriers with some amount of overlap/crosstalk between them such as (i) carrier reuse-within-cell (RWC), also called Space-Division Multiple Access (SDMA) because of the need for an antenna array to spatially discriminate co-channel signals; (ii) Code-Division Multiple Access (CDMA) systems where multiple users transmit in the same band using distinct codes; and (iii) Time-Division Multiple Access (TDMA) and/or Frequency-Division Multiple Access (FDMA) systems where users are not perfectly separable in time and/or frequency, i.e. they interfere with one another either in time (e.g. because of dispersive channels) and/or in frequency (e.g. because of excess bandwidth due to imperfect channel filtering) thus leading to adjacent-channel interference (ACI).
Mathematical expressions in this patent specification are based upon complex baseband notation.
Array antenna radio receivers typically are employed at the base stations or access points of digital communications systems (e.g. mobile telephone networks, broadband wireless access for Internet and/or wide-area networking, etc.) to improve reception link quality (i.e provide robustness against multipath fading) and/or reduce interference levels, where interference can include thermal noise and man-made signals which exist in the desired signal's band. Since such systems typically accommodate large numbers of simultaneously active users in any given cell or sector, the base station receiver must be capable of maintaining a plurality of radio links.
Known antenna array radio receiver systems comprise an array of antenna elements coupled to a signal receiving section (also referred to as a radio-frequency (RF) front-end) which in turn is coupled to a signal processing section. The signal receiving section processes the branch signals from the different antenna elements independently, in separate branches, and performs on each branch signal standard downconversion, demodulation, filtering to isolate the channel of interest and, possibly, some transformation on the signal to bring it to a form usable by the signal processing section (e.g. analog-to-digital conversion if the signal processor is digital). The signal processor takes the information from all of the branches (i.e. the demodulated, filtered and suitably transformed signal data from each individual antenna element) and, using one of a number of appropriate known techniques, combines and processes it to extract a useful signal y(t), which is the best possible estimate of the desired user signal s0(t).
In the context of wireless communications, the received vector x(t) (i.e. the received signal across all array elements) is made up of a desired signal s0(t) transmitted by a “desired user's” wireless terminal, interfering signals sm(t) transmitted by competing terminals which operate in the same frequency band or in adjacent bands with some amount of crosstalk being present, and white noise n(t). Hence, in non-dispersive (i.e. narrowband) environments
                                          x            ⁡                          (              t              )                                =                                                                      c                  0                                ⁡                                  (                  t                  )                                            ⁢                                                s                  0                                ⁡                                  (                  t                  )                                                      +                                          ∑                                  m                  =                  1                                M                            ⁢                                                                    c                    m                                    ⁡                                      (                    t                    )                                                  ⁢                                                      s                    m                                    ⁡                                      (                    t                    )                                                                        +                          n              ⁡                              (                t                )                                                    ,                            (        1        )            where cm(t) is an N×1 vector of complex elements describing the channel from the mth terminal to all of the N array elements, M is the number of interfering signals, n(t) is the white thermal noise vector, and c0(t) is an N×1 complex vector describing the channel from the 0th terminal which, by convention, is that of the desired user.
In such a context, the function of the antenna array radio receiver is to isolate the desired user signal s0(t) from the interferers and white noise as well as compensate for distortions introduced in the channel c0(t) (e.g. multipath fading) so that, at all times, the array output signal y(t) approximates the desired user signal s0(t) as closely as possible.
Typically, the receiver combines the branch signals from the individual antenna elements simply by means of a linear weight-and-sum operation. If an N-element array is considered and x(t) is the N×1 vector of the array element outputs, the array output is defined asy(t)=wH(t)x(t),  (2)where w(t) is the N×1 complex weight vector and (•)H denotes the Hermitian transpose (i.e. complex conjugate transpose of its argument, be it a vector (as it is in the above) or a matrix).
Although it is time-varying, the weight vector varies slowly compared to the input and output signals, since it tracks changes in the channels, not in the signals themselves. When a combiner operates according to equation (2), it is termed a linear combiner and the entire receiver is designated a linear array receiver.
Typically, the receiver collects statistics of the input signal x(t) and uses them to derive a weight vector which minimizes some error measure between the array output y(t) and the desired signal s0(t). One of the most common error measures in such applications (i.e. adaptive filtering) is the mean-square errorε=<[y(t)−s0(t)]2>=<[wH(t)x(t)−s0(t)]2>,  (3)which forms an N-dimensional quadratic surface with respect to the weight vector elements. The minimization of this criterion forms the basis of minimum mean-square error (MMSE) linear array receivers (also called optimum combiners).
(Note: Henceforth, the dependence upon time t in equations will be omitted for the sake of clarity.)
Adaptive filtering theory indicates that the best combination of weights in the MMSE for a given sequence of received data isw=Rxx−1c0  (4)where Rxx is the covariance matrix of the received array outputs and is given byRxx=<xxH>,  (5)where (•) denotes the expectation (i.e. the ensemble average) of its argument.
Such array receivers are suitable for use where tine dispersion due to multipath propagation does not extend significantly beyond a single symbol period. That is, there is little or no intersymbol interference (ISI).
When the channels carrying useful signals do exhibit significant ISI, the traditional solution is to use an equalizer, which is an adaptive filter whose purpose is to invert the channel impulse response (thus untangling the ISI) so that the overall impulse response at its output will tend to be much shorter in time and have an ideal, flat (or equalized) frequency spectrum.
The signal processing portion of the standard linear equalizer works in the same way as a linear adaptive array receiver except that the signal sources, i.e., the elements of the input vector x, are not points in space (i.e. the array of antenna elements) but points in time. The signals are tapped at a series of points along a symbol-spaced delay line (termed a tapped-delay line or TDL), then weighted and combined.
While the implementation of the signal processing apparatus for both the equalizer and the array receiver can be identical (minimization of the MSE by adaptive weighting of the inputs), the performance will differ. Because signals are physically sampled at different points in space by the array receiver, it is very effective at nulling unwanted signal sources or co-channel interference (CCI). However, it has limited ability against intersymbol interference (ISI) due to dispersive, i.e. frequency-selective, fading, since the latter is spread in time. On the other hand, the equalizer is adept at combatting ISI but has limited ability against CCI.
In environments where both ISI and CCI are present, array reception and equalization may be combined to form a space-time array receiver. The most general form of the latter is obtained when each weighting multiplier in a narrow band array receiver is replaced by a full equalizer for a total of N equalizers. Again the implementation of the signal processing section will be similar and will rely on equation (2) supra. The only difference is that the weight vector w and the input vector x will each be longer. Indeed, for an equalizer length of L taps and an array size of N elements, the vectors w and x will both have LN elements.
The canonical linear mean-square-error minimizing space-time receiver (i.e. the most obvious and immediate linear space-time receiver structure and also in certain respects the most complex) comprises an antenna array where each array element output is piped to a finite impulse response (FIR) adaptive filter, which in this context is referred to as an equalizer. Each adaptive filter comprises a tapped-delay line where taps are spaced by a symbol period or a fraction of a symbol period. For good performance, the length of the tapped-delay line should be equal or superior to the average channel memory length. In many cases, the number of taps this implies can be very large (e.g. 10-100 per adaptive filter).
The weights multiplying each tap output must be constantly adapted to follow the changes in the channel(s) characteristics. This can be performed in various ways, either with continuous or block-based adaptation and with or without the support of known training symbols. In most known systems, the weights are computed on a block-by-block basis (block adaptation) and each block contains a sequence of known training symbols for that purpose. In digital wireless communications, the block used for adaptation purposes will typically correspond to a data packet as defined by the networking protocol in use. Moreover, the channels can be considered static over the length of a block (i.e., the length of a block is significantly smaller than the channel correlation time).
By adapting the weights to minimize a global performance index, e.g. the mean-square error between the desired signal and the S-T receiver output, the receiver usually performs the following:                reduces or eliminates intersymbol interference (ISI) caused by frequency-selective fading in wideband channels;        reduces or eliminates co-channel interference (CCI) from nearest cells where carriers are reused or from inside the cell (since the space-time processor permits reuse of carriers within cell—or sector—thanks to its power of spatial discrimination—often referred to as space division multiple-access (SDMA));        improves output SNR (due to the array's larger effective aperture).        
Since wireless systems are typically interference-limited (i.e., interference is the main impediment which prevents capacity increase—accommodating more active users—above a certain limit), the first two benefits of space-time processors are mainly of interest in order to increase capacity.
To achieve maximal benefit, it is better to combine the S-T array with carrier reuse-within-cell (RWC). A number of previous patents disclose arrays (see, for example U.S. Pat. Nos. 5,515,378 and 5,592,490) or space-time systems (see, for example, U.S. Pat. No. 5,828,658) applied in an SDMA (i.e. RWC) context. In such a system, separate S-T processors will have to be implemented for every user (all processors share the same physical antenna array and front-end receiver circuitry but have distinct equalizers and combiners). However, the base station has information (received symbols, channel characteristics) available about in-cell interferers since each in-cell interferer is another local S-T processor's desired signal.
S-T processor architectures can be formulated to exploit this multiuser information by establishing some type of connectivity between individual S-T processors to achieve one of two goals:                improve performance (reduced bit-error rate, improved interference nulling, etc.);        reduce complexity and cost.        
It is known to exploit multiuser information to perform “joint detection” of many users, for example by constructing a global multiuser MSE criterion, thus improving performance of an array receiver (with respect to single user detection) at the cost of increased complexity [2], [3].
It is also known that, with appropriate space-time processing, it is possible to combine SDMA with adequate temporal processing to mitigate the intersymbol interference (ISI) present in wideband dispersive channels [6].
One of the main disadvantages of previously-known space-time processing receivers is their great complexity and cost, especially if multiuser detection is employed and/or temporal processing employed.
It is known to reduce bandwidth requirements in forward-channel probing transmitters by tracking only long-term variations in the channels (i.e., the subspace structure) [11] but that approach is not applicable in receivers without seriously limiting user capacity.